Simple Energy-Aware Algorithms for Selecting a Server in a Scalable Cluster

It is critical to reduce the electric energy consumption of servers in a cluster. In this paper, we discuss a migration approach to reducing the electric energy consumption of servers where a virtual machine with application processes migrates to a more energy-efficient server. In this paper, we consider a homogeneous cluster. We newly propose an ISEAM2H algorithm. Here, a virtual machine on a host server is selected to perform a process issued by an application and a guest server to which a virtual machine migrates is found so that the total electric energy consumption of servers can be minimized. In the evaluation, we show the total electric energy consumption and active time of the servers and the average execution time of processes can be reduced in the ISEAM2H algorithm.

In our previous studies, the dynamic virtual machine migration (DVMM) algorithm is proposed to reduce the total electric energy consumption of servers by migrating virtual machines to more energy-efficient servers. Here, virtual machines are dynamically created and dropped depending on number of processes. However, the more number of virtual machines are created, the more number of virtual machines are dropped. Servers consume the electric energy to drop virtual machines. In this paper, we propose an IDVMM (improved DVMM) algorithm to decrease the number of virtual machines to be dropped. In the evaluation, we show not only the total electric energy consumption and active time of servers but also the average execution time of processes can be reduced in the IDVMM algorithm compared with other algorithms.

The MVCC (Multi-Version Concurrency Control) is so far proposed to increase the concurrency of multiple conflicting transactions and the scalability of a distributed system. However, the larger number of transactions are concurrently performed, the larger amount of electric energy is consumed by servers in a system. In our previous studies, the EEMVTO (Energy-Efficient Multi-Version Timestamp Ordering) algorithm is proposed to not only reduce the total electric energy consumption of servers but also increase the throughput of a system by not performing meaningless write methods on each object. In this paper, the IEEMVTO (Improved EEMVTO) algorithm is newly proposed to furthermore reduce the total electric energy consumption of servers by not performing meaningless read methods in addition to meaningless write methods. The evaluation results show the total electric energy consumption of servers can be more reduced in the IEEMVTO algorithm than the EEMVTO algorithm.KeywordsMulti-version concurrency controlEnergy-Efficient Multi-Version Timestamp Ordering (EEMVTO)Improved EEMVTO (IEEMVTO) algorithmObject-based systemTransaction

In order to fault-tolerantly perform an application process in a server cluster, the process is replicated on multiple servers. Even if some replicas of the process is faulty, e.g. due to stop-fault of the host server, the process can be successfully performed as long as some number of replicas are operational. The more number of replicas of a process are performed, the more reliably and availably the process can be performed but the more electric energy is consumed. In this paper, we make clear what software components each replica of a process includes. We newly propose new replication schemes which are composed of a primary replica and more types of secondary replicas so that the total electric energy consumption can be reduced while the reliability and availability of each process can be increased. In the evaluation, we show the electric energy consumption of servers can be reduced in the replication schemes compared with the traditional active and passive replication schemes.

Processes on virtual machines can migrate from a host server to a guest server by migrating the virtual machines. In this paper, we propose a DMMV (Dynamic Migration of Multiple Virtual machines) algorithm where virtual machines migrate from a host server to a more energy-efficient guest server. Here, virtual machines are dynamically suspended and resumed depending on the number of processes. In addition, one or more than one virtual machine is selected to migrate from a host server to a guest server. The number of virtual machines to migrate is decided so as to minimize the electric energy consumption of the host and guest servers. In the evaluation, we show not only the total electric energy consumption and active time of servers but also the average execution time of processes can be reduced in the DMMV algorithm compared with other algorithms.

The electric power consumed by servers has to be reduced in a cluster in order to realize eco society. We take a macro level approach to reducing the total electric energy consumption of servers to perform application processes in a server cluster. Servers are now equipped with multi-core CPUs. In this paper, we discuss a multi-level power consumption (MLPC) model of a server with a multi-core CPU. Here, the power consumption of a server depends on the number of active cores and active threads where at least one application process is performed. We also discuss a multi-level computation (MLC) model which gives the expected execution time of a process which is concurrently performed with other processes on a server with a multi-core CPU. Based on the MLPC model and the MLC model, we discuss an energy-aware (EA) algorithm to select a server for each process requested by a client in a cluster so as to reduce the total electric energy consumption while satisfying deadline requirements of the processes. We evaluate the EA algorithm and show not only the total energy consumption but also the average execution time of each process is reduced in the EA algorithm compared with the round-robin (RR) and random (RD) algorithms.

The electric power consumed by servers has to be reduced in order to realize green societies. We consider computation (CP) and storage (ST) types of application processes performed on servers in this paper, where CPU and storage drives are mainly consumed, respectively. The authors proposed the storage-based power consumption (SBPC) model and storage-based computation (SBCP) model to perform ST and CP processes on a server. Here, the power consumption rate Et( ) [W] of a server st at time depends on types of processes which are concurrently performed but is independent of the number of the processes on the server st in the SBPC model. The average execution time of a CP process depends on the numbers of CP processes concurrently performed and the average execution time of an ST process depends on the number of concurrent ST and CP processes in the SBCP model. By using the SBPC and SBCP models, we enhance the energy aware (EA) algorithm for selecting a server for each CP/ST process so that not only the execut n time of each process but also the power consumption of servers can be reduced. We show the evaluation of the EA algorithm in terms of the total power consumption and average execution time. Keywords-Power consumption models, Energy-aware (EA) selection algorithm, Storage-based power consumption (SBPC) model, Storage-based computation (SBCP) model.

Internet of Things (IoT) revolution seems a promising technology to create new tools and options to decrease electrical energy consumption in buildings of any type. It is planned to publish series of articles dealing both with electrical and heat energy multi-point measurements and consumption reduction options. This is first article, showing current studies, obtained findings and first results, focusing on industrial and office type building electrical energy consumption, definition of problems and description of possible experimental solution.

The national demand for primary energy has experienced an average increase of almost 5% in recent years, driven by the growth in electricity consumption, which grew by an average of 6% per year between 2003 and 2017, by virtue of the almost generalization of rural electrification and the dynamism of our economy and especially the policy of major works in infrastructure, industry, agriculture, tourism, and social housing. In fact, forecasting the demand for electrical energy remains a controversial issue in the development of the electricity grid and energy management. The ARIMA (1, 1, 1) model is applied to model electrical energy consumption for the annual period from 1971 to 2020. The same data are also used to predicting for 2021–2030 in order to verify the adequacy of the model and to provide information on the state of energy demand in Morocco in the future. The main results indicate an upward trend in electrical energy consumption by the end of 2030, with electricity consumption expected to be in the range of 2039639.09–53589.00 GWh per year.

In order to realize green society, we take the process migration approach to reducing the total electric energy consumption of clusters by migrating virtual machines. In our previous studies, the DM (Dynamic Migration) algorithm is proposed where virtual machines are dynamically resumed and suspended and a group of virtual machines on a host server migrate to a guest server so that the total energy consumption of the host and guest servers can be reduced. In this paper, we newly propose a DGM (Dynamic Group Migration) algorithm. Here, there is a seed virtual machine on each server. A virtual machine is created as a clone of the seed virtual machine so that the number of processes on each virtual machine is kept fewer. In the evaluation, we show the total electric energy consumption of servers can be more reduced in the DGM algorithm compared with other algorithms.

The electric arc furnace operation at the Štore Steel company, one of the largest flat spring steel producers in Europe, consists of charging, melting, refining the chemical composition, adjusting the temperature, and tapping. Knowledge of the consumed energy within the individual electric arc operation steps is essential. The electric energy consumption during melting and refining was analyzed including the maintenance and technological delays. In modeling the electric energy consumption, 25 parameters were considered during melting (e.g., coke, dolomite, quantity), refining and tapping (e.g., injected oxygen, carbon, and limestone quantity) that were selected from 3248 consecutively produced batches in 2018. Two approaches were employed for the data analysis: linear regression and genetic programming model. The linear regression model was used in the first randomly generated generations of each of the 100 independent developed civilizations. More accurate models were subsequently obtained during the simulated evolution. The average relative deviation of the linear regression and the genetic programming model predictions from the experimental data were 3.60% and 3.31%, respectively. Both models were subsequently validated by using data from 278 batches produced in 2019, where the maintenance and the technological delays were below 20 minutes per batch. It was possible, based on the linear regression and the genetically developed model, to calculate that the average electric energy consumption could be reduced by up to 1.04% and 1.16%, respectively, in the case of maintenance and other technological delays.

Electrical energy affect to economic, electrical energy consumption will increase and decrease likely economics. In this globalization era, electricity consumption was increased trend yearly since industrialization era. The reliability Electrical energy is very important for economic growth. The lower SAIDI and SAIFI is the bench mark for reliability of electrical energy supply. The reliable of insulator cover type: YSL-70-AP affect to the reliability electrical distribution energy on over head distribution circuit. Insulator cover protected to over head distribution circuit againt animal, bird, tree ang other temporary disturbance. Insulator cover also to protect half insulated medium voltage cable againt partial discharge and flashover.   Over voltage stress more often during operation, to impact to the material insulation performance. This quantitative research founding:  insulator cover type: YSL-70-AP still feasible to use after voltage breakdown stress. The fault current is still under the maximum allowable leakage current (11,600 micro ampere) which is 41.61 micro ampere, and breakdown voltage is still   higher than minimum that specified (24 kilo volt), which is 49.63 kilo volt. Post breakdown voltage the material insulation performance of insulator cover type: YSL-70-AP is good, and reliable to continuous operation over head distribution circuit.

Bu çalışmanın amacı Türkiye’de yenilenebilir elektrik enerjisi üretimine etki eden faktörleri araştırmaktır. Bu amaçla 1998-2014 yılları arası Türkiye’nin yenilenebilir elektrik enerjisi üretimi, toplam elektrik enerjisi tüketimi, toplam elektrik enerjisi tüketimi içerisinde yenilenebilir enerji tüketiminin payı ve kişi başına Gayri Safi Yurt İçi Hâsıla yıllık büyüme oranı verileri Dünya Bankası verilerinden elde edilmiştir. OLS tahmin modeli kullanılarak yapılan analiz sonucunda Türkiye’de toplam elektrik enerjisi tüketiminin, toplam elektrik enerjisi tüketimi içerisinde yenilenebilir enerji tüketiminin payının ve kişi başına GSYH’nin yenilenebilir elektrik enerjisi üretimine anlamlı ve pozitif yönde katkı sağladığı bulunmuştur. Yenilenebilir elektrik enerjisi üretimi ile kişi başına GSYH büyüme hızı arasında pozitif yönde çift yönlü nedensellik bulunmuştur. Dahası, toplam elektrik enerjisi tüketimi değişkeni ile toplam elektrik enerjisi tüketimi içerisinde yenilenebilir enerji tüketiminin payının değişkenleri hem yenilenebilir elektrik enerjisi üretimini hem de kişi başına GSYH büyüme hızı değişkenlerini tek yönlü olarak pozitif yönde etkilemektedir.

This research introduces a dual design proportional–integral–derivative (PID) controller architecture process that aims to improve system performance by reducing overshoot and conserving electrical energy. The dual design PID controller uses real-time error and one-time step delay to adjust the confidence weights of the controller, leading to improved performance in reducing overshoot and saving electrical energy. To evaluate the effectiveness of the dual design PID controller, experiments were conducted to compare it with the PID controller using least overshoot tuning by Chien–Hrones–Reswick (CHR) technique. The results showed that the dual design PID controller was more effective at reducing overshoot and saving electrical energy. A case study was also conducted as part of this research, and it demonstrated that the system performed better when using the dual design PID controller. Overshoot and electrical energy consumption are common issues in systems that can impact performance, and the dual design PID controller architecture process provides a solution to these issues by reducing overshoot and saving electrical energy. The dual design PID controller offers a new technique for addressing these issues and improving system performance. In summary, this research presents a new technique for addressing overshoot and electrical energy consumption in systems through the use of a dual design PID controller. The dual design PID controller architecture process was found to be an effective solution for reducing overshoot and saving electrical energy in systems, as demonstrated by the experiments and case study conducted as part of this research. The dual design PID controller presents a promising solution for improving system performance by addressing the issues of overshoot and electrical energy consumption.

Scalable, high performance, and fault-tolerant distributed applications are realized with virtual machines in server cluster systems. Application processes are performed on virtual machines in each server. Processing load of virtual machines to perform application processes has to be balanced in a server cluster system to satisfy the application requirements like response time. On the other hand, a server cluster system consumes a large amount of electric energy since multiple servers consume electric energy to perform application processes. It is critical to discuss how to reduce the total electric energy consumption of a server cluster to perform application processes on virtual machines. In our previous studies, the transmission model and power consumption model of a server to perform communication processes on multiple virtual machines are proposed. In this paper, we newly propose the transmission energy consumption laxity based (TECLB) algorithm to allocate communication processes to virtual machines in a server cluster based on the proposed transmission model and power consumption model of a server so that the total energy consumption of a server cluster can be reduced. We evaluate the TECLB algorithm in terms of the total energy consumption of a server cluster and transmission time of each process compared with the basic round-robin (RR) algorithm. The evaluation results show the average total energy consumption of a server cluster is maximumly reduced to 9% of the RR algorithm.